背景:越来越多的研究表明,DNMTs(DNMT1、DNMT3A和DNMT3B)的单核苷酸多态性(SNPs)的异常变化与多种肿瘤的发生或减少有关。然而,DNMT变异与胃癌(GC)风险之间的关联仍然存在冲突.我们旨在评估DNMTs多态性对GC易感性的影响。
方法:首先,我们对7个SNP进行了荟萃分析(DNMT1中的rs16999593,rs2228611,rs8101866,DNMT3A中的rs1550117,rs13420827,rs1569686,rs2424913在DNMT3B中)。四种遗传模型(纯合子,杂合子,使用显性和隐性模型)。此外,我们进行了荟萃敏感性和亚组分析,以阐明异质性来源.最后,系统评价中提供了17个无法进行荟萃分析的SNP。
结果:纳入了20项研究,13项研究可以进行荟萃分析,7项研究不能。首先,对13项研究(3959例GC病例和5992例对照)进行的7个SNPs的荟萃分析显示,rs16999593(杂合子模型:OR1.36,95CI1.14-1.61;显性模型:OR1.36,95CI1.15-1.60)和rs1550117(纯合子模型:OR2.03,95CI1.38-3.00模型:OR1.95-1.69显性0.其余SNP未发现与GC风险相关。此外,亚组分析表明,对于rs1550117和rs1569686,在中国江苏省的人群中尤其发现了显着关联(rs1550117,OR1.77,95CI1.25-2.51;rs1569686,OR0.48,95CI0.36-0.64),PCR-RFLP是发现显着关联的敏感方法(rs1550117,OR1.77,r95686s0.95-2.51最后,对17个SNPs的7项研究进行的系统评价表明,rs36012910,rs7560488和rs6087990可能对GC的引发有潜在影响.
结论:这项荟萃分析表明,rs16999593和rs1550117可能导致GC风险,rs1569686可能是胃癌发生的保护因素。通过使用这些SNP作为生物标志物,估计获取GC的风险,从而制定及时的预防策略是可行的。
BACKGROUND: Increasing studies showed that abnormal changes in single nucleotide polymorphisms (SNPs) of DNMTs (DNMT1, DNMT3A and DNMT3B) were associated with occurrence or decrease of various tumors. However, the associations between DNMTs variations and gastric cancer (GC) risk were still conflicting. We aimed to assess the effect of DNMTs polymorphisms on the susceptibility to GC.
METHODS: Firstly, we did a meta-analysis for 7 SNPs (rs16999593, rs2228611, rs8101866 in DNMT1, rs1550117, rs13420827 in DNMT3A, rs1569686, rs2424913 in DNMT3B). Four genetic models (homozygote, heterozygote, dominant and recessive model) were used. Moreover, a meta-sensitivity and subgroup analysis was performed to clarify heterogeneity source. Lastly, 17 SNPs that couldn\'t be meta-analyzed were presented in a systematic
review.
RESULTS: 20 studies were included, 13 studies could be meta-analyzed and 7 ones could not. Firstly, a meta-analysis on 13 studies (3959 GC cases and 5992 controls) for 7 SNPs showed that GC risk increased in rs16999593 (heterozygote model: OR 1.36, 95%CI 1.14-1.61; dominant model: OR 1.36, 95%CI 1.15-1.60) and rs1550117 (homozygote model: OR 2.03, 95%CI 1.38-3.00; dominant model: OR 1.20, 95%CI 1.01-1.42; recessive model: OR 1.96, 95%CI 1.33-2.89) but decreased in rs1569686 (dominant model: OR 0.74, 95%CI 0.61-0.90). The remaining SNPs were not found associated with GC risk. Furthermore, the subgroup analysis indicated that for rs1550117 and rs1569686, the significant associations were particularly found in people from Chinese Jiangsu province (rs1550117, OR 1.77, 95%CI 1.25-2.51; rs1569686, OR 0.48, 95%CI 0.36-0.64) and that PCR-RFLP was a sensitive method to discover significant associations (rs1550117, OR 1.77, 95%CI 1.25-2.51; rs1569686, OR 0.49, 95%CI 0.37-0.65). Lastly, a systematic
review on 7 studies for 17 SNPs suggested that rs36012910, rs7560488 and rs6087990 might have a potential effect on GC initiation.
CONCLUSIONS: This meta-analysis demonstrated that rs16999593 and rs1550117 could contribute to GC risk and that rs1569686 might be a protective factor against gastric carcinogenesis. By using these SNPs as biomarkers, it is feasible to estimate the risk of acquiring GC and thus formulate timely preventive strategy.